一种基于非线性频谱分析的故障预报技术及应用

首先改进了一种非线性系统广义频率响应函数(GFRF)的辨识算法,提高了辨识结果的精度和鲁棒性,并依此提出了一种基于非线性频谱分析的非线性系统早期故障预报方法.然后,利用该方法对某型直升机并联电动舵机进行了实际故障预报.多次的实际检测结果表明了该早期故障预报方法的有效性.该方法的特点是:算法简单,计算量小,适合于在线故障检测和预报,可为一大类非线性系统的早期故障预报研究提供一种新途径,有着广阔的工程应用前景.

A Nonlinear Spectral Analysis Based Fault Forecasting Method and Its Application

An identification arithmetic for the generalized frequency response function (GFRF) is modified firstly in this paper to improve the accuracy and robustness of this identification method, and then, a fault forecasting method based on nonlinear spectral analysis is proposed and is applied into the fault forecasting of certain helicopters electric rudders. Many times of experiments indicate that this fault forecasting method is effective in fault forecasting. The feature of this fault forecasting method is that the arithmetic of this method is simple and that no heavy computation is needed. This characteristic makes this method suitable for online fault forecasting. And this fault foresting method supplies a new solution to the fault forecasting of a large class of nonlinear systems and has a broad prospect for practical application.